library(tidyverse)
library(dplyr)
library(ggplot2)
library(sf)
list.files()
[1] "Atlantico" "Bogotá D.C" "Ciudades" "Ciudades_Ciudadesxd.nb.html" "Ciudades_Ciudadesxd.Rmd"
[6] "co.csv" "Colombia.qgz" "EjemploQGISXD.qgz" "EVA" "MapaPutumayo.Rmd"
[11] "MGN2017_08_ATLANTICO.rar" "MGN2017_11_BOGOTA.rar" "MGN2017_86_PUTUMAYO.rar" "Putumayo" "PutumayoEVA.nb.html"
[16] "PutumayoEVA.Rmd" "QGIS" "rsconnect"
eva_putumayo <- read_csv("EVA/Evaluaciones_Agropecuarias_Putumayo_EVA.csv")
Rows: 1776 Columns: 17
-- Column specification ----------------------------------------------------------------------------------------------------------------------------------
Delimiter: ","
chr (10): DEPART, MUNIC, GRUPO_DE_CULTIVO, SUBGRUPO_DE_CULTIVO, CULTIVO, SISTEMA, PERIODO, ESTADO_FISICO_PRODUCCION, NOMBRE_
CIENTIFICO, CICLO_DE_CUL...
dbl (6): COD_DEPT, YEAR, HA_SEMBRADA, HA_COSECHADA, PRODUCCION, RENDIMIENTO
i Use `spec()` to retrieve the full column specification for this data.
i Specify the column types or set `show_col_types = FALSE` to quiet this message.
eva_putumayo
mun_putumayo <- sf::st_read("E:/Descargas en el disco duro/4to Semestre/Geomatica/Putumayo/ADMINISTRATIVO/MGN_MPIO_POLITICO.shp")
Reading layer `MGN_MPIO_POLITICO' from data source `E:\Descargas en el disco duro\4to Semestre\Geomatica\Putumayo\ADMINISTRATIVO\MGN_MPIO_POLITICO.shp' using driver `ESRI Shapefile'
Simple feature collection with 13 features and 9 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: -77.18681 ymin: -0.5622776 xmax: -73.84132 ymax: 1.467315
Geodetic CRS: WGS 84
mun_putumayo$KM2 <- st_area(st_transform(mun_putumayo, 3116))/1E6
mun_putumayo$KM2 <- as.numeric(mun_putumayo$KM2)
mun_putumayo$KM2 <- round(mun_putumayo$KM2,3)
min(mun_putumayo$KM2)
[1] 64.275
max(mun_putumayo$KM2)
[1] 10906.88
library(leaflet)
bins <- c(60, 150, 500, 1000, 2500, 5000, 7500, 10000, 11000)
pal <- colorBin("RdYlGn", domain = mun_putumayo$KM2, bins = bins)
mapa <- leaflet(data = mun_putumayo) %>%
addTiles() %>%
addPolygons(label = ~KM2,
popup = ~MPIO_CNMBR,
fillColor = ~pal(KM2),
color = "#444444",
weight = 1,
smoothFactor = 0.5,
opacity = 1.0,
fillOpacity = 0.5,
highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
) %>%
addProviderTiles(providers$OpenStreetMap) %>%
addLegend("bottomright", pal = pal, values = ~KM2,
title = "Extensión Municipal [Km2] (DANE, 2018)",
opacity = 1
)
mapa
class(mun_putumayo$MPIO_CCDGO)
[1] "character"
class(eva_putumayo$COD_MUN)
[1] "numeric"
mun_putumayo$COD_MUN <- as.double(mun_putumayo$MPIO_CCDGO)
class(mun_putumayo$COD_MUN)
[1] "numeric"
platano_putumayo <- eva_putumayo %>% filter(CULTIVO == "PLATANO") %>% dplyr::select(MUNIC, COD_MUN, YEAR, PERIODO, PRODUCCION, RENDIMIENTO)
platano_putumayo
yuca_putumayo <- eva_putumayo %>% filter(CULTIVO == "YUCA") %>% dplyr::select(MUNIC, COD_MUN, YEAR, PERIODO, PRODUCCION, RENDIMIENTO)
yuca_putumayo
maiz_putumayo <- eva_putumayo %>% filter(SISTEMA == "MAIZ TRADICIONAL") %>% dplyr::select(MUNIC, COD_MUN, YEAR, PERIODO, PRODUCCION, RENDIMIENTO)
maiz_putumayo
summary(platano_putumayo)
MUNIC COD_MUN YEAR PERIODO PRODUCCION RENDIMIENTO
Length:108 Min. :86001 Min. :2007 Length:108 Min. : 250 Min. :2.200
Class :character 1st Qu.:86568 1st Qu.:2010 Class :character 1st Qu.: 1150 1st Qu.:4.600
Mode :character Median :86571 Median :2012 Mode :character Median : 1788 Median :5.260
Mean :86568 Mean :2012 Mean : 4128 Mean :5.555
3rd Qu.:86757 3rd Qu.:2015 3rd Qu.: 6262 3rd Qu.:6.133
Max. :86885 Max. :2018 Max. :17600 Max. :9.780
summary(yuca_putumayo)
MUNIC COD_MUN YEAR PERIODO PRODUCCION RENDIMIENTO
Length:108 Min. :86001 Min. :2007 Length:108 Min. : 75.0 Min. : 4.00
Class :character 1st Qu.:86568 1st Qu.:2010 Class :character 1st Qu.: 932.2 1st Qu.: 7.00
Mode :character Median :86571 Median :2012 Mode :character Median :1586.5 Median : 8.50
Mean :86568 Mean :2012 Mean :2377.2 Mean : 8.77
3rd Qu.:86757 3rd Qu.:2015 3rd Qu.:3375.0 3rd Qu.:10.00
Max. :86885 Max. :2018 Max. :8730.0 Max. :13.00
summary(maiz_putumayo)
MUNIC COD_MUN YEAR PERIODO PRODUCCION RENDIMIENTO
Length:251 Min. :86001 Min. :2006 Length:251 Min. : 4.0 Min. :0.600
Class :character 1st Qu.:86568 1st Qu.:2009 Class :character 1st Qu.: 132.0 1st Qu.:1.000
Mode :character Median :86571 Median :2012 Mode :character Median : 270.0 Median :1.200
Mean :86572 Mean :2012 Mean : 380.4 Mean :1.247
3rd Qu.:86757 3rd Qu.:2015 3rd Qu.: 405.0 3rd Qu.:1.400
Max. :86885 Max. :2018 Max. :2000.0 Max. :3.000
platano_putumayo %>% replace(is.na(.), 0) -> platano_putumayo2
platano_putumayo %>% group_by(MUNIC, COD_MUN, YEAR) %>%
summarize(PRODUCCION=sum(PRODUCCION)) -> platano_putumayo2
head(platano_putumayo2)
tail(platano_putumayo2)
platano_putumayo2 %>%
group_by(COD_MUN) %>%
gather("PRODUCCION", key = variable, value = number) %>%
unite(combi, variable, YEAR) %>%
pivot_wider(names_from = combi, values_from = number, values_fill = 0) -> platano_putumayo3
head(platano_putumayo3)
tail(platano_putumayo3)
mun_putumayo_platano = left_join(mun_putumayo, platano_putumayo3, by="COD_MUN")
summary(mun_putumayo_platano)
DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng Shape_Area
Length:13 Length:13 Length:13 Length:13 Min. : 64.28 Min. :2017 Length:13 Min. :0.4549 Min. :0.005209
Class :character Class :character Class :character Class :character 1st Qu.: 379.74 1st Qu.:2017 Class :character 1st Qu.:1.1755 1st Qu.:0.030778
Mode :character Mode :character Mode :character Mode :character Median : 926.47 Median :2017 Mode :character Median :1.7197 Median :0.075139
Mean : 1998.18 Mean :2017 Mean :2.3357 Mean :0.162151
3rd Qu.: 1939.39 3rd Qu.:2017 3rd Qu.:2.4752 3rd Qu.:0.157171
Max. :10906.88 Max. :2017 Max. :7.5377 Max. :0.885758
KM2 COD_MUN MUNIC PRODUCCION_2007 PRODUCCION_2008 PRODUCCION_2009 PRODUCCION_2010 PRODUCCION_2011 PRODUCCION_2012 PRODUCCION_2013
Min. : 64.28 Min. :86001 Length:13 Min. : 510 Min. : 445 Min. : 250 Min. : 507 Min. : 450 Min. : 500 Min. : 737
1st Qu.: 379.74 1st Qu.:86568 Class :character 1st Qu.: 1431 1st Qu.: 1328 1st Qu.: 920 1st Qu.: 1380 1st Qu.: 1290 1st Qu.: 1450 1st Qu.: 1260
Median : 926.47 Median :86573 Mode :character Median : 2360 Median : 2400 Median : 2750 Median : 2835 Median : 2790 Median : 2010 Median : 1500
Mean : 1998.18 Mean :86584 Mean : 4230 Mean : 4543 Mean : 4130 Mean : 4581 Mean : 4410 Mean : 4412 Mean : 4176
3rd Qu.: 1939.39 3rd Qu.:86757 3rd Qu.: 5070 3rd Qu.: 4450 3rd Qu.: 5460 3rd Qu.: 4995 3rd Qu.: 6250 3rd Qu.: 5670 3rd Qu.: 6300
Max. :10906.88 Max. :86885 Max. :13773 Max. :17600 Max. :17280 Max. :17280 Max. :17184 Max. :17280 Max. :16320
NA's :4 NA's :4 NA's :4 NA's :4 NA's :4 NA's :4 NA's :4
PRODUCCION_2014 PRODUCCION_2015 PRODUCCION_2016 PRODUCCION_2017 PRODUCCION_2018 geometry
Min. : 787 Min. : 1095 Min. : 388 Min. : 260 Min. : 321 POLYGON :13
1st Qu.: 1300 1st Qu.: 1148 1st Qu.: 1080 1st Qu.: 847 1st Qu.: 935 epsg:4326 : 0
Median : 1664 Median : 1400 Median : 1150 Median : 1508 Median : 1775 +proj=long...: 0
Mean : 4359 Mean : 4159 Mean : 4220 Mean : 3064 Mean : 3250
3rd Qu.: 6400 3rd Qu.: 6400 3rd Qu.: 6448 3rd Qu.: 2924 3rd Qu.: 3910
Max. :16320 Max. :16320 Max. :16320 Max. :10610 Max. :10750
NA's :4 NA's :4 NA's :4 NA's :4 NA's :4
head(mun_putumayo_platano[,1:10])
Simple feature collection with 6 features and 10 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: -77.18681 ymin: 0.2391261 xmax: -76.41003 ymax: 1.467315
Geodetic CRS: WGS 84
DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng Shape_Area KM2
1 86 86001 MOCOA 1958 1304.63835 2017 PUTUMAYO 2.4752281 0.105792947 1304.638
2 86 86219 COLÓN Decreto 2830 de Diciembre 2 de 1989 64.27462 2017 PUTUMAYO 0.4548864 0.005209533 64.275
3 86 86320 ORITO Decreto 2891 de Diciembre 28 de 1978 1939.39517 2017 PUTUMAYO 2.1520883 0.157171417 1939.391
4 86 86749 SIBUNDOY Decreto 1871 de Julio 1 de 1982 97.73462 2017 PUTUMAYO 0.5113819 0.007922269 97.735
5 86 86755 SAN FRANCISCO Decreto 2830 de Diciembre 2 de 1989 407.35674 2017 PUTUMAYO 1.1754950 0.033022563 407.357
6 86 86757 SAN MIGUEL (La Dorada) Ordenanza 45 de Abril 29 de 1994 379.74249 2017 PUTUMAYO 1.3275843 0.030777834 379.743
geometry
1 POLYGON ((-76.6705 1.467315...
2 POLYGON ((-76.96835 1.28631...
3 POLYGON ((-77.07275 0.94231...
4 POLYGON ((-76.9043 1.299191...
5 POLYGON ((-76.87345 1.28986...
6 POLYGON ((-76.99677 0.37418...
tail(mun_putumayo_platano[,1:10])
Simple feature collection with 6 features and 10 fields
Geometry type: POLYGON
Dimension: XY
Bounding box: xmin: -77.11293 ymin: -0.5622776 xmax: -73.84132 ymax: 1.075532
Geodetic CRS: WGS 84
DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng Shape_Area KM2
8 86 86865 VALLE DEL GUAMUEZ Decreto DAINCO 3293 de Noviembre 12 de 1985 815.1590 2017 PUTUMAYO 1.715066 0.06606599 815.162
9 86 86885 VILLAGARZÓN Decreto 574 de Marzo 14 de 1977 1396.9664 2017 PUTUMAYO 1.928017 0.11325718 1396.972
10 86 86569 PUERTO CAICEDO Ordenanza 12 de Noviembre 24 de 1992 926.4672 2017 PUTUMAYO 1.719718 0.07513926 926.466
11 86 86568 PUERTO ASÍS Decreto 1951 de Octubre 24 de 1967 2819.1573 2017 PUTUMAYO 3.644402 0.22867909 2819.154
12 86 86571 PUERTO GUZMÁN Ordenanza 13 de Noviembre 24 de 1992 4576.5912 2017 PUTUMAYO 4.734632 0.37145875 4576.592
13 86 86573 PUERTO LEGUÍZAMO Decreto 698 de Noviembre 13 de 1953 10906.8838 2017 PUTUMAYO 7.537728 0.88575793 10906.878
geometry
8 POLYGON ((-77.00282 0.50363...
9 POLYGON ((-76.63426 1.06411...
10 POLYGON ((-76.41069 0.86694...
11 POLYGON ((-76.2263 0.638888...
12 POLYGON ((-75.94095 1.02942...
13 POLYGON ((-75.20032 0.47930...
library(RColorBrewer)
library(leaflet)
bins <- c(0, 500, 1000, 2500, 5000, 10000, 15000, 20000)
pal <- colorBin("YlOrRd", domain = mun_putumayo_platano$PRODUCCION_2018, bins = bins)
mapa1 <- leaflet(data = mun_putumayo_platano) %>%
addTiles() %>%
addPolygons(label = ~PRODUCCION_2018,
popup = ~MPIO_CNMBR,
fillColor = ~pal(PRODUCCION_2018),
color = "#444444",
weight = 1,
smoothFactor = 0.5,
opacity = 1.0,
fillOpacity = 0.5,
highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
) %>%
addProviderTiles(providers$OpenStreetMap) %>%
addLegend("bottomright", pal = pal, values = ~PRODUCCION_2018,
title = "Producción del cultivo de Platano [Ton] (2018)",
opacity = 1
)
mapa1
yuca_putumayo %>% replace(is.na(.), 0) -> yuca_putumayo2
yuca_putumayo %>% group_by(MUNIC, COD_MUN, YEAR) %>%
summarize(PRODUCCION=sum(PRODUCCION)) -> yuca_putumayo2
yuca_putumayo2 %>%
group_by(COD_MUN) %>%
gather("PRODUCCION", key = variable, value = number) %>%
unite(combi, variable, YEAR) %>%
pivot_wider(names_from = combi, values_from = number, values_fill = 0) -> yuca_putumayo3
head(yuca_putumayo3)
tail(yuca_putumayo3)
mun_putumayo_yuca = left_join(mun_putumayo, yuca_putumayo3, by="COD_MUN")
summary(mun_putumayo_yuca)
DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng Shape_Area
Length:13 Length:13 Length:13 Length:13 Min. : 64.28 Min. :2017 Length:13 Min. :0.4549 Min. :0.005209
Class :character Class :character Class :character Class :character 1st Qu.: 379.74 1st Qu.:2017 Class :character 1st Qu.:1.1755 1st Qu.:0.030778
Mode :character Mode :character Mode :character Mode :character Median : 926.47 Median :2017 Mode :character Median :1.7197 Median :0.075139
Mean : 1998.18 Mean :2017 Mean :2.3357 Mean :0.162151
3rd Qu.: 1939.39 3rd Qu.:2017 3rd Qu.:2.4752 3rd Qu.:0.157171
Max. :10906.88 Max. :2017 Max. :7.5377 Max. :0.885758
KM2 COD_MUN MUNIC PRODUCCION_2007 PRODUCCION_2008 PRODUCCION_2009 PRODUCCION_2010 PRODUCCION_2011 PRODUCCION_2012 PRODUCCION_2013
Min. : 64.28 Min. :86001 Length:13 Min. : 882 Min. :1140 Min. :1102 Min. : 770 Min. : 812 Min. : 585 Min. : 666
1st Qu.: 379.74 1st Qu.:86568 Class :character 1st Qu.:3190 1st Qu.:2000 1st Qu.:1534 1st Qu.:1120 1st Qu.:1132 1st Qu.:1235 1st Qu.: 935
Median : 926.47 Median :86573 Mode :character Median :3360 Median :3200 Median :2700 Median :1534 Median :1564 Median :2025 Median :1770
Mean : 1998.18 Mean :86584 Mean :4108 Mean :3518 Mean :2976 Mean :2110 Mean :1872 Mean :2259 Mean :2036
3rd Qu.: 1939.39 3rd Qu.:86757 3rd Qu.:4500 3rd Qu.:6000 3rd Qu.:4560 3rd Qu.:2700 3rd Qu.:2880 3rd Qu.:3060 3rd Qu.:2970
Max. :10906.88 Max. :86885 Max. :8412 Max. :6160 Max. :6120 Max. :6120 Max. :3500 Max. :4800 Max. :4500
NA's :4 NA's :4 NA's :4 NA's :4 NA's :4 NA's :4 NA's :4
PRODUCCION_2014 PRODUCCION_2015 PRODUCCION_2016 PRODUCCION_2017 PRODUCCION_2018 geometry
Min. : 544 Min. : 280 Min. : 105 Min. : 140 Min. : 75 POLYGON :13
1st Qu.: 978 1st Qu.: 954 1st Qu.: 420 1st Qu.: 424 1st Qu.: 480 epsg:4326 : 0
Median :1280 Median :1375 Median : 797 Median : 686 Median : 910 +proj=long...: 0
Mean :2221 Mean :2309 Mean :2129 Mean :1508 Mean :1480
3rd Qu.:3105 3rd Qu.:3420 3rd Qu.:3500 3rd Qu.:1600 3rd Qu.:1200
Max. :5850 Max. :6305 Max. :8730 Max. :6510 Max. :7000
NA's :4 NA's :4 NA's :4 NA's :4 NA's :4
bins <- c(0, 500, 1000, 2500, 5000, 8000, 10000)
pal <- colorBin("YlOrRd", domain = mun_putumayo_yuca$PRODUCCION_2018, bins = bins)
mapa2 <- leaflet(data = mun_putumayo_yuca) %>%
addTiles() %>%
addPolygons(label = ~PRODUCCION_2018,
popup = ~MPIO_CNMBR,
fillColor = ~pal(PRODUCCION_2018),
color = "#777777",
weight = 1,
smoothFactor = 0.5,
opacity = 1.0,
fillOpacity = 0.5,
highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
) %>%
addProviderTiles(providers$OpenStreetMap) %>%
addLegend("bottomright", pal = pal, values = ~PRODUCCION_2018,
title = "Producción del cultivo de Yuca [Ton] (2018)",
opacity = 1
)
mapa2
maiz_putumayo %>% replace(is.na(.), 0) -> maiz_putumayo2
maiz_putumayo %>% group_by(MUNIC, COD_MUN, YEAR) %>%
summarize(PRODUCCION=sum(PRODUCCION)) -> maiz_putumayo2
`summarise()` has grouped output by 'MUNIC', 'COD_MUN'. You can override using the `.groups` argument.
maiz_putumayo2 %>%
group_by(COD_MUN) %>%
gather("PRODUCCION", key = variable, value = number) %>%
unite(combi, variable, YEAR) %>%
pivot_wider(names_from = combi, values_from = number, values_fill = 0) -> maiz_putumayo3
head(maiz_putumayo3)
head(maiz_putumayo3)
mun_putumayo_maiz = left_join(mun_putumayo, maiz_putumayo3, by="COD_MUN")
summary(mun_putumayo_maiz)
DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng Shape_Area
Length:13 Length:13 Length:13 Length:13 Min. : 64.28 Min. :2017 Length:13 Min. :0.4549 Min. :0.005209
Class :character Class :character Class :character Class :character 1st Qu.: 379.74 1st Qu.:2017 Class :character 1st Qu.:1.1755 1st Qu.:0.030778
Mode :character Mode :character Mode :character Mode :character Median : 926.47 Median :2017 Mode :character Median :1.7197 Median :0.075139
Mean : 1998.18 Mean :2017 Mean :2.3357 Mean :0.162151
3rd Qu.: 1939.39 3rd Qu.:2017 3rd Qu.:2.4752 3rd Qu.:0.157171
Max. :10906.88 Max. :2017 Max. :7.5377 Max. :0.885758
KM2 COD_MUN MUNIC PRODUCCION_2007 PRODUCCION_2008 PRODUCCION_2009 PRODUCCION_2010 PRODUCCION_2011 PRODUCCION_2012
Min. : 64.28 Min. :86001 Length:13 Min. : 80 Min. : 81.0 Min. : 132 Min. : 0.0 Min. : 0.0 Min. : 0.0
1st Qu.: 379.74 1st Qu.:86568 Class :character 1st Qu.: 378 1st Qu.: 253.0 1st Qu.: 276 1st Qu.: 250.0 1st Qu.: 291.0 1st Qu.: 60.0
Median : 926.47 Median :86573 Mode :character Median : 515 Median : 417.0 Median : 704 Median : 440.0 Median : 634.0 Median :291.0
Mean : 1998.18 Mean :86584 Mean :1015 Mean : 763.7 Mean : 930 Mean : 775.6 Mean : 864.2 Mean :297.1
3rd Qu.: 1939.39 3rd Qu.:86757 3rd Qu.: 904 3rd Qu.: 820.0 3rd Qu.:1127 3rd Qu.: 795.0 3rd Qu.: 803.0 3rd Qu.:387.0
Max. :10906.88 Max. :86885 Max. :3784 Max. :2730.0 Max. :2677 Max. :2677.0 Max. :3150.0 Max. :772.0
PRODUCCION_2013 PRODUCCION_2014 PRODUCCION_2015 PRODUCCION_2016 PRODUCCION_2017 PRODUCCION_2018 PRODUCCION_2006 geometry
Min. : 0.0 Min. :107.0 Min. :170 Min. : 44.0 Min. : 54.0 Min. : 6.0 Min. : 0.0 POLYGON :13
1st Qu.: 92.0 1st Qu.:176.0 1st Qu.:223 1st Qu.: 132.0 1st Qu.: 175.0 1st Qu.: 114.0 1st Qu.: 0.0 epsg:4326 : 0
Median : 236.0 Median :236.0 Median :264 Median : 230.0 Median : 240.0 Median : 268.0 Median : 386.0 +proj=long...: 0
Mean : 323.6 Mean :309.1 Mean :357 Mean : 408.2 Mean : 480.1 Mean : 372.1 Mean : 448.8
3rd Qu.: 407.0 3rd Qu.:390.0 3rd Qu.:428 3rd Qu.: 350.0 3rd Qu.: 549.0 3rd Qu.: 385.0 3rd Qu.: 513.0
Max. :1295.0 Max. :855.0 Max. :918 Max. :2486.0 Max. :2557.0 Max. :2000.0 Max. :1706.0
bins <- c(0, 50, 100, 250, 500, 1000, 1500, 2000)
pal <- colorBin("YlOrRd", domain = mun_putumayo_maiz$PRODUCCION_2018, bins = bins)
mapa3 <- leaflet(data = mun_putumayo_maiz) %>%
addTiles() %>%
addPolygons(label = ~PRODUCCION_2018,
popup = ~MPIO_CNMBR,
fillColor = ~pal(PRODUCCION_2018),
color = "#444444",
weight = 1,
smoothFactor = 0.5,
opacity = 1.0,
fillOpacity = 0.5,
highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
) %>%
addProviderTiles(providers$OpenStreetMap) %>%
addLegend("bottomright", pal = pal, values = ~PRODUCCION_2018,
title = "Producción del cultivo de Maiz Tradicional [Ton] (2018)",
opacity = 1
)
mapa3
---
title: "PutumayoEVA"
author: "Gabriel de Jesus Romero Diaz"
date: "26-oct/2021"
output: html_notebook
---

```{r message=FALSE}
library(tidyverse)
library(dplyr)
library(ggplot2)
library(sf)
```

```{r}
list.files()
```



```{r show_col_types=FALSE}
eva_putumayo <- read_csv("EVA/Evaluaciones_Agropecuarias_Putumayo_EVA.csv")
```


```{r}
eva_putumayo
```
```{r}
mun_putumayo <- sf::st_read("E:/Descargas en el disco duro/4to Semestre/Geomatica/Putumayo/ADMINISTRATIVO/MGN_MPIO_POLITICO.shp")
```

```{r}
mun_putumayo$KM2 <- st_area(st_transform(mun_putumayo, 3116))/1E6
```

```{r}
mun_putumayo$KM2 <- as.numeric(mun_putumayo$KM2)
```

```{r}
mun_putumayo$KM2 <- round(mun_putumayo$KM2,3)
```

```{r}
min(mun_putumayo$KM2)
```
```{r}
max(mun_putumayo$KM2)
```
```{r}
library(leaflet)
bins <- c(60, 150, 500, 1000, 2500, 5000, 7500, 10000, 11000)
pal <- colorBin("RdYlGn", domain = mun_putumayo$KM2, bins = bins)

  mapa <- leaflet(data = mun_putumayo) %>%
  addTiles() %>%
  addPolygons(label = ~KM2,
              popup = ~MPIO_CNMBR,
              fillColor = ~pal(KM2),
              color = "#444444",
              weight = 1,
              smoothFactor = 0.5,
              opacity = 1.0,
              fillOpacity = 0.5,
              highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
              ) %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addLegend("bottomright", pal = pal, values = ~KM2,
    title = "Extensión Municipal [Km2] (DANE, 2018)",
    opacity = 1
  )
```

```{r}
mapa
```
```{r}
class(mun_putumayo$MPIO_CCDGO)
```
```{r}
class(eva_putumayo$COD_MUN)
```
```{r}
mun_putumayo$COD_MUN <-  as.double(mun_putumayo$MPIO_CCDGO)
```

```{r}
class(mun_putumayo$COD_MUN)
```

```{r}
platano_putumayo <- eva_putumayo %>%  filter(CULTIVO == "PLATANO")  %>%  dplyr::select(MUNIC, COD_MUN, YEAR, PERIODO, PRODUCCION, RENDIMIENTO) 
```


```{r}
platano_putumayo
```
```{r}
yuca_putumayo <- eva_putumayo %>%  filter(CULTIVO == "YUCA")  %>%  dplyr::select(MUNIC, COD_MUN, YEAR, PERIODO, PRODUCCION, RENDIMIENTO)

yuca_putumayo
```

```{r}
maiz_putumayo <- eva_putumayo %>%  filter(SISTEMA == "MAIZ TRADICIONAL")  %>%  dplyr::select(MUNIC, COD_MUN, YEAR, PERIODO, PRODUCCION, RENDIMIENTO)

maiz_putumayo
```
```{r}
summary(platano_putumayo)
```
```{r}
summary(yuca_putumayo)
```

```{r}
summary(maiz_putumayo)
```

```{r}
platano_putumayo %>% replace(is.na(.), 0) -> platano_putumayo2
```

```{r}
platano_putumayo %>% group_by(MUNIC, COD_MUN, YEAR) %>%
   summarize(PRODUCCION=sum(PRODUCCION)) -> platano_putumayo2
```

```{r}
head(platano_putumayo2)
```

```{r}
tail(platano_putumayo2)
```

```{r}
platano_putumayo2 %>% 
  group_by(COD_MUN) %>% 
  gather("PRODUCCION", key = variable, value = number)   %>% 
  unite(combi, variable, YEAR) %>%
  pivot_wider(names_from = combi, values_from = number, values_fill = 0) -> platano_putumayo3                                                                   
```

```{r}
head(platano_putumayo3)
```
 
```{r}
tail(platano_putumayo3)
```

```{r}
mun_putumayo_platano = left_join(mun_putumayo, platano_putumayo3, by="COD_MUN")
```

```{r}
summary(mun_putumayo_platano)
```
```{r}
head(mun_putumayo_platano[,1:10])
```

```{r}
tail(mun_putumayo_platano[,1:10])
```


```{r}
library(RColorBrewer)
library(leaflet)
```

```{r}
bins <- c(0, 500, 1000, 2500, 5000, 10000, 15000, 20000)
pal <- colorBin("YlOrRd", domain = mun_putumayo_platano$PRODUCCION_2018, bins = bins)

  mapa1 <- leaflet(data = mun_putumayo_platano) %>%
  addTiles() %>%
  addPolygons(label = ~PRODUCCION_2018,
              popup = ~MPIO_CNMBR,
              fillColor = ~pal(PRODUCCION_2018),
              color = "#444444",
              weight = 1,
              smoothFactor = 0.5,
              opacity = 1.0,
              fillOpacity = 0.5,
              highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
              ) %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addLegend("bottomright", pal = pal, values = ~PRODUCCION_2018,
    title = "Producción del cultivo de Platano [Ton] (2018)",
    opacity = 1
  )
```

```{r}
mapa1
```

```{r}
yuca_putumayo %>% replace(is.na(.), 0) -> yuca_putumayo2
```

```{r}
yuca_putumayo %>% group_by(MUNIC, COD_MUN, YEAR) %>%
   summarize(PRODUCCION=sum(PRODUCCION)) -> yuca_putumayo2
```

```{r}
yuca_putumayo2 %>% 
  group_by(COD_MUN) %>% 
  gather("PRODUCCION", key = variable, value = number)   %>% 
  unite(combi, variable, YEAR) %>%
  pivot_wider(names_from = combi, values_from = number, values_fill = 0) -> yuca_putumayo3  
```

```{r}
head(yuca_putumayo3)
```

```{r}
head(yuca_putumayo3)
```

```{r}
mun_putumayo_yuca = left_join(mun_putumayo, yuca_putumayo3, by="COD_MUN")
```

```{r}
summary(mun_putumayo_yuca)
```

```{r}
bins <- c(0, 500, 1000, 2500, 5000, 8000, 10000)
pal <- colorBin("YlOrRd", domain = mun_putumayo_yuca$PRODUCCION_2018, bins = bins)

  mapa2 <- leaflet(data = mun_putumayo_yuca) %>%
  addTiles() %>%
  addPolygons(label = ~PRODUCCION_2018,
              popup = ~MPIO_CNMBR,
              fillColor = ~pal(PRODUCCION_2018),
              color = "#777777",
              weight = 1,
              smoothFactor = 0.5,
              opacity = 1.0,
              fillOpacity = 0.5,
              highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
              ) %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addLegend("bottomright", pal = pal, values = ~PRODUCCION_2018,
    title = "Producción del cultivo de Yuca [Ton] (2018)",
    opacity = 1
  )
```

```{r}
mapa2
```

```{r}
maiz_putumayo %>% replace(is.na(.), 0) -> maiz_putumayo2
```

```{r}
maiz_putumayo %>% group_by(MUNIC, COD_MUN, YEAR) %>%
   summarize(PRODUCCION=sum(PRODUCCION)) -> maiz_putumayo2
```
```{r}
maiz_putumayo2 %>% 
  group_by(COD_MUN) %>% 
  gather("PRODUCCION", key = variable, value = number)   %>% 
  unite(combi, variable, YEAR) %>%
  pivot_wider(names_from = combi, values_from = number, values_fill = 0) -> maiz_putumayo3  
```

```{r}
head(maiz_putumayo3)
```

```{r}
head(maiz_putumayo3)
```

```{r}
mun_putumayo_maiz = left_join(mun_putumayo, maiz_putumayo3, by="COD_MUN")
```

```{r}
summary(mun_putumayo_maiz)
```
```{r}
bins <- c(0, 50, 100, 250, 500, 1000, 1500, 2000)
pal <- colorBin("YlOrRd", domain = mun_putumayo_maiz$PRODUCCION_2018, bins = bins)

  mapa3 <- leaflet(data = mun_putumayo_maiz) %>%
  addTiles() %>%
  addPolygons(label = ~PRODUCCION_2018,
              popup = ~MPIO_CNMBR,
              fillColor = ~pal(PRODUCCION_2018),
              color = "#444444",
              weight = 1,
              smoothFactor = 0.5,
              opacity = 1.0,
              fillOpacity = 0.5,
              highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
              ) %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addLegend("bottomright", pal = pal, values = ~PRODUCCION_2018,
    title = "Producción del cultivo de Maiz Tradicional [Ton] (2018)",
    opacity = 1
  )
```

```{r}
mapa3
```














































